Citrus tristeza virus (CTV) affects citrus crops with differing severity, depending on the viral strain, the citrus cultivar and the scion/rootstock combinations. In this study we address the problem of identifying asymptomatic infected plants using reflectance spectra of the leaves in the visible/near infrared region. Sixteen young citrus plants (8 Citrus x clementina hort. ex Tanaka ‘Fina’ and 8 Citrus sinensis (L.) Osbeck ‘Valencia Late’) were split into control and T318A isolate infected groups. Measurements of reflectance in the 400-1100 nm range, in two leaves per plant, were performed monthly over 6 months and the presence of the virus was confirmed by IC/RT-PCR and real-time PCR. The spectra acquired in a single day of measurements was inconsistent for inoculated and control plants. However, by monitoring the same leaves over 6 months it was possible to identify infected plants on the basis of the spectra time evolution. In order to achieve this a simple unfolding implementation of 3-way PCA was applied such that group separation in the scores plot was spontaneous and not forced by any a priori assumption. The model was tested through leave-one-out cross validation with a good rate of correct classification for the left out sample. A real situation was simulated by applying the NPCA algorithm to healthy plants only and checking if the infected ones would be projected on the model scores plot as outliers. Again, a good rate of classification was obtained. Finally, we discuss the spectral features that may be associated with the clustering obtained through NPCA and their physiological significance. Reflectance measurements between infected and healthy samples of two citrus cultivars and their correlation with real-time PCR results for the presence of CTV suggest reflectance spectra of the leaves in the visible/near infrared region is a promising tool for plant stress monitoring linked to the presence of CTV infection prior to symptom expression.